Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
Frontiers

Efficient vegetation filtering method using K-means clustering algorithm: case study of high steep rock slope

Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...
IEEE

Accelerating Spherical K-Means Clustering for Large-Scale Sparse Document Data

Abstract: This paper presents an accelerated spherical Kmeans clustering algorithm for large-scale and high-dimensional sparse document data sets. We design an algorithm working in an ...
IEEE

A Topological-Indicators-Based k-Means Clustering Algorithm and Its Application in Time Series Data: A Case Study on Sea Level Variability in Peninsular Malaysia

Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
Scientific Research Publishing

Ikotun, A. M., Ezugwu, A. E., Abualigah, L., Abuhaija, B., & Heming, J. (2023). K-means Clustering Algorithms: A Comprehensive Review, Variants Analysis, and Advances in the ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...
Scientific Research Publishing

Domain Delineation Using Geological Data, Variogram Analysis, and Clustering Algorithms ()

1 Facultad de Ingeniería, Universidad Andres Bello, Santiago, Chile. 2 Department of Mining Engineering, Universidad de Chile, Santiago, Chile. 3 Advanced Mining Technology Center, Universidad de ...